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Python
3.0
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What is Python ?
Python is a general purpose, dynamic, high level and interpreted programming language. It supports Object
Oriented programming approach to develop applications.
Python supports multiple programming pattern, including object oriented, imperative and functional or
procedural programming styles.
Python is not intended to work on special area such as web programming. That is why it is known as
multipurpose because it can be used with web, enterprise, 3D CAD etc.
We don't need to use data types to declare variable because it is dynamically typed so we can write a=10 to
assign an integer value in an integer variable.
Python makes the development and debugging fast because there is no compilation step included in python
development and edit-test-debug cycle is very fast.

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Compiler Vs Interpreter
Compiler Interpreter
Scans the entire program and translates it as a
whole into machine code.
Translates program one statement at a time.
It takes large amount of time to analyze the
source code but the overall execution time is
comparatively faster.
It takes less amount of time to analyze the
source code but the overall execution time is
slower.
Generates intermediate object code which
further requires linking, hence requires more
memory.
No intermediate object code is generated,
hence are memory efficient.
It generates the error message only after
scanning the whole program. Hence
debugging is comparatively hard.
Continues translating the program until the
first error is met, in which case it stops. Hence
debugging is easy.
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Python History
The implementation of Python was started in the December 1989 by Guido Van Rossum at CWI in
Netherland.
In February 1991, van Rossum published the code (labeled version 0.9.0) to alt. sources.
In 1994, Python 1.0 was released with new features like: lambda, map, filter, and reduce.
Python 2.0 added new features like: list comprehensions, garbage collection system.
On December 3, 2008, Python 3.0 (also called "Py3K") was released. It was designed to rectify
fundamental flaw of the language.
ABC language & Modula-3
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Python Features
Easy to Learn and Use
Expressive Language
Interpreted Language
Cross-platform Language
Free and Open Source
Object-Oriented Language
GUI Programming Support
Large Standard Library
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• Dynamically Typed
• Embedded
Flavors of Python:
1.CPython: It is the standard flavor of Python. It can be used to work
with C lanugage Applications
2. Jython or JPython: It is for Java Applications. It can run on JVM
3. IronPython: It is for C#.Net platform
4.PyPy: The main advantage of PyPy is performance will be improved because JIT compiler is
available inside PVM.
5.RubyPython For Ruby Platforms
6. AnacondaPython It is specially designed for handling large volume of data processing.

Python Applications
Web Applications
Desktop GUI Applications
Software Development
Scientific and Numeric
Business Applications
Console Based Application
Audio or Video based Applications
3D CAD Applications
Applications for Images
Enterprise Applications

Python Versions
Python Version Released Date
Python 1.0 January 1994
Python 1.5 December 31, 1997
Python 1.6 September 5, 2000
Python 2.0 October 16, 2000
Python 2.1 April 17, 2001
Python 2.3 July 29, 2003
Python 2.4 November 30, 2004
Python 2.6 October 1, 2008
Python 2.7 July 3, 2010
Python 3.1 June 27, 2009
Python 3.2 February 20, 2011
Python 3.4 March 16, 2014
Python 3.6.4 December 19, 2017

Python 2.X vs 3.X
DIVISION OPERATOR
PRINT FUNCTION Xrange
Error Handling

Python Identifiers
A Python identifier is a name used to identify a variable, function, class, module, or other object. An identifier
starts with a letter A to Z or a to z, or an underscore (_) followed by zero or more letters, underscores and digits
(0 to 9). Python does not allow punctuation characters such as @, $, and % within identifiers. Python is a case
sensitive programming language. Thus, Car and car are two different identifiers in Python.
Here are naming conventions for Python identifiers:
• Class names start with an uppercase letter. All other identifiers start with a
lowercase letter.
• Starting an identifier with a single leading underscore indicates that the
identifier is private.
• Starting an identifier with two leading underscores indicates a strongly private
identifier.
• If the identifier also ends with two trailing underscores, the identifier is a
language-defined special name.

Identifiers
1. The only allowed characters in Python are :===
• alphabet symbols(either lower case or upper case)
• digits(0 to 9)
• underscore symbol(_)
2. By mistake if we are using any other symbol like $
then we will get syntax error.
cash = 10
ca$h =20
3. Identifier should not starts with digit
123total
total123
4.Identifiers are case sensitive. Of course Python
language is case sensitive language. total=10
TOTAL=999
print(total) #10
print(TOTAL) #999
1. Alphabet Symbols (Either Upper case OR Lower case)
2. If Identifier is start with Underscore (_) then it indicates it
is private.
3. Identifier should not start with Digits.
4. Identifiers are case sensitive.
5. We cannot use reserved words as identifiers Eg:
def=10
6. There is no length limit for Python identifiers. But not
recommended to use too lengthy identifiers.
7. Dollor ($) Symbol is not allowed in Python.

Keywords in Python
Program:
Output:

Lines and Indentation
Python provides no braces to indicate blocks of code for class and function definitions or
flow control. Blocks of code are denoted by line indentation, which is rigidly enforced.
Multi-line statements
Statements in Python typically end with a new line. Python does, however, allow the use of
the line continuation character () to denote that the line should continue. For example:

Quotation in Python
Python accepts single ('), double (") and triple (''' or """) quotes to denote string
literals, as long as the same type of quote starts and ends the string.
Triple quotes are also used for multiple line comments

Variables in Python
Variables are nothing but reserved memory locations to store values. This means
when you create a variable, you reserve some space in memory.
Python variables do not need explicit declaration to reserve memory space. The
declaration happens automatically when you assign a value to a variable. The equal sign (=) is
used to assign values to variables.

Multiple Assignment in Python
Python allows you to assign a single value to several variables simultaneously. For
example:

Input and Output in Python
We use the print() function to output data to the standard output device (screen). To allow flexibility we
might want to take the input from the user. In Python, we have the input() function to allow this.
Read multiple values from the keyboard in a single
line.
split() function can take space as separator by default
.But we can pass anything as separator.

Python Data Types
Python has various standard data types that are used to define the operations possible on them and
the storage method for each of them. Data Type represent the type of data present inside a variable.
In Python we are not required to specify the type explicitly. Based on value provided,the type will be
assigned automatically.Hence Python is Dynamically Typed Language.
Python has five standard data types:
•Numbers
•String
•Boolean
•List
•Tuple
•Set
•Dictionary
• bytes
• Bytearray
• range
• None

28/07/2022
In Python everything is object
We can represent int values in the
following ways
1. Decimal form 2. Binary form
3. Octal form 4. Hexa decimal form
1. Decimal form(base-10):
It is the default number system in Python The allowed digits
are: 0 to 9 Eg: a =10
2. Binary form(Base-2):
The allowed digits are : 0 & 1 Literal value should be prefixed
with 0b or 0B
Eg: a = 0B1111 a =0B123 a=b111
3. Octal Form(Base-8):
The allowed digits are : 0 to 7 Literal value should be prefixed
with 0o or 0O.
a=0o123
a=0o786
4. Hexa Decimal Form(Base-16):
The allowed digits are : 0 to 9, a-f (both lower and upper cases
are allowed) Literal value should be prefixed with 0x or 0X
Eg: a =0XFACE a=0XBeef a =0XBeer
Python contains several inbuilt functions
1.type() -- to check the type of variable
2. id() -- to get address of object
3. print() -- to print the value

Base Conversion
1.bin(): We can use bin() to convert from any base to binary.
bin(15)
'0b1111'
bin(0o11)
'0b1001'
bin(0X10)
'0b10000'
2. oct(): We can use oct() to convert from any base to octal.
oct(10)
'0o12'
oct(0B1111)
'0o17'
oct(0X123)
'0o443'
3.hex(): We can use hex() to convert from any base to hexa decimal
hex(100)
'0x64'
hex(0B111111)
'0x3f'
hex(0o12345)
'0x14e5'
Note >>: f=1.2e3
print(f) 1200.0 instead of 'e' we can use 'E‘
The main advantage of exponential form is we can represent
big values in less memory
Complex -- Complex data type has some inbuilt attributes to retrieve
the real part and imaginary part.
a=10+1.5j
b=20+2.5j
c=a+b
c=10.5+3.6j
c.real==>10.5 c.imag==>3.6
bool data type: We can use this data type to
represent boolean values. The only allowed values for
this data type are: True and False
Internally Python represents True as 1 and False as 0
True+True==>2 ,True-False==>1
Python provide the following in-built functions for base conversions.

Python Numbers
Python supports four different numerical types:
•int (signed integers)
•long (long integers, they can also be represented in octal and
hexadecimal)
•float (floating point real values)
•complex (complex numbers)
To Delete a number to a reference we can use del

Python Numbers
eval(): eval Function take a String and
evaluate the Result.

PythonStrings
Strings in Python are identified as a contiguous set of characters represented in the quotation marks.
Python allows for either pairs of single or double quotes. Subsets of strings can be taken using the slice
operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -
1 at the end. The plus (+) sign is the string concatenation operator and the asterisk (*) is the
repetition operator.
a = ‘Something’
b = “Something”
c = '''This "Python class very helpful“
for java students'''
Slicing of Strings: Slice means a piece [ ] operator is called slice operator,which can be used to retrieve parts of String. In Python
Strings follows zero based index. The index can be either +ve or -ve. +ve index means forward direction from Left to Right -ve
index means backward direction from Right to Left.
a = “Entertainment”
a1 = a[0]
a2 = a[-1]
a3 = a[2:5]
a4 = a[2,6,2]
a5 = a[-1]
a6 = a[-5:-1]
a7 = a[: :-1]
Note -- long Data Type is available in Python2 but not in Python3. In
Python3 long values also we can represent by using int type only.

Python Escape Sequence Charact
er
Use
' Single quote (')
" Double quote (")
a ASCII Bell (BEL)
b ASCII Backspace (BS)
f ASCII Formfeed (FF)
n ASCII Linefeed (LF)
r
ASCII Carriage
Return (CR)
t
ASCII Horizontal Tab
(TAB)
v
ASCII Vertical Tab
(VT)
u Unicode
x Hexcode
Escape characters are characters that are generally used to
perform certain tasks and their usage in code directs the
compiler to take a suitable action mapped to that character.
Repr():----This function returns a string in its
printable format, i.e doesn’t resolve the
escape sequences.

Python Lists
Lists are one of the most powerful tools in python. They are just like the arrays
declared in other languages. But the most powerful thing is that list need not
be always homogenous. A single list can contain strings, integers, as well as
objects. Lists can also be used for implementing stacks and queues. If we want
to represent a group of values as a single entity where insertion order required
to preserve and duplicates are allowed then we should go for list data type.
1. insertion order is preserved
2. heterogeneous objects are allowed
3. duplicates are allowed
4. Growable in nature
5. values should be enclosed within square brackets.

List Operations
Note:-list is growable in nature. i.e based on our
requirement we can increase or decrease the size.
Note: An ordered, mutable, heterogenous collection of
eleemnts is nothing but list, where duplicates also
allowed.

Python Tuples
A tuple is another sequence data type that is similar to the list. A tuple consists of a number of
values separated by commas. Unlike lists, however, tuples are enclosed within parentheses.
The main differences between lists and tuples are: Lists are enclosed in brackets [ ] and their
elements and size can be changed, while tuples are enclosed in parentheses ( ) and cannot be
updated. Tuples can be thought of as readonly lists.
Note: tuple is the read only version of list .

Python Dictionary
In python, dictionary is similar to hash or maps in other languages. It consists of key value pairs. The value
can be accessed by unique key in the dictionary. If we want to represent a group of values as key-value pairs
then we should go for dict data type.
Duplicate keys are not allowed but values can be duplicated. If we are trying to insert an entry with duplicate
key then old value will be replaced with new value.
Note:
1. In general we can use bytes and bytearray data types to represent binary information like images,video files etc
2. In Python2 long data type is available. But in Python3 it is not available and we can represent long values also by
using int type only.
3. Python there is no char data type. Hence we can represent char values also by using str type.

Range
range Data Type represents a sequence of numbers. The elements present in range Data type
are not modifiable. i.e range Data type is immutable.

Byte Type
Python supports a range of types to store sequences. There are six sequence
types: strings, byte sequences (bytes objects), byte arrays (bytearray objects),
lists, tuples, and range objects.
Bytes and bytearray objects contain single bytes – the former is immutable while
the latter is a mutable sequence. Bytes objects can be constructed the
constructor, bytes(), and from literals; use a b prefix with normal string syntax:
b'python'. To construct byte arrays, use the bytearray() function.
Note bytes data type represens a group of byte numbers just like an array.
Byte type Return a new "bytes" object, which is an immutable sequence of small
integers in the range 0 <= x < 256, print as ASCII characters when displayed.
bytes is an immutable version of bytearray – it has the same non-mutating
methods and the same indexing and slicing behavior.

Byte Array
The only allowed values for byte data type are 0 to 256. By mistake if we are trying to provide any other values then
we will get value error.
Once we creates bytes data type value, we cannot change its values,otherwise we will get TypeError.
Note:----bytearray is exactly same as bytes data type except that its elements can be modified.

Sets
A Set is an unordered collection data type that is iterable, mutable, and has no duplicate
elements. Python’s set class represents the mathematical notion of a set.
The major advantage of using a set, as opposed to a list, is that it has a highly optimized
method for checking whether a specific element is contained in the set.
• Sets are unordered.
• Set elements are unique. Duplicate elements are not allowed.
• A set itself may be modified, but the elements contained in the set must be of an
immutable type.
Properties regarding Sets:----
1. insertion order is not preserved
2. duplicates are not allowed
3. heterogeneous objects are allowed
4. index concept is not applicable
5. It is mutable collection
6. Growable in nature
Frozen Sets Frozen sets are immutable objects that only support methods and operators
that produce a result without affecting the frozen set or sets to which they are applied.

Mutable and Immutable Data Types
In general, data types in Python can be distinguished based on whether objects of the type are mutable
or immutable. The content of objects of immutable types cannot be changed after they are created.
Only mutable objects support methods that change the object in place, such as reassignment of a
sequence slice, which will work for lists, but raise an error for tuples and strings.It is important to
understand that variables in Python are really just references to objects in memory
Some immutable
types
Some mutable types
•int, float, complex
•str
•bytes
•tuple
•frozenset
•bool
•array
•bytearray
•list
•set
•Dict

Python Arithmetic Operators
Operator
+ Addition
- Subtraction
* Multiplication
/ Divison
% Modulus
** Exponent
// Floor Divison
Note:operator always performs floating point arithmetic.
. Hence it will always returns float value. But Floor division (//) can
perform both floating point
and integral arithmetic. If arguments are int type then result is int
type. If atleast one argument
is float type then result is float type

Python Relational Operators
Opera
tor
Example
== If(a==n) then True
> If(a>n) then True
< If(a<n) then True
>= If(a>=n) then True
<= If(a<=n) then True
!= If(a!=n) then True
<> If(a<>n) then True
Relational operators are symbols that perform operations on data
and return a result as true or false depending on the comparison
conditions. Thus, they are certain functionalities that do something with your variables.
Chaining of relational operators is possible. In the chaining, if all comparisons returns
True then only result is True. If atleast one comparison returns False then the result is
False

Python Assignment Operators
Eg: a+=2 ====> a = a+2

Ternary operator
Python ternary operator is also termed as conditional operator. This is
because it can evaluate a statement with a condition being true or false.
Python ternary operator
• Python ternary operaator was introduced in Python 2.5.
• If used properly, ternary operator can reduce code size and increase
readability of the code.
• There is no special keyword for ternary operator, it’s the way of writing
if-else statement that creates a ternary statement or conditional
expression.

Python Bitwise Operators
Operator
& (AND)
| (OR)
^ (XOR)
~ (Binary Ones Complement)
<< (Binary Left Shift)
>> (Binary Right Shift)
We can apply these operators bitwise. These operators are applicable only for
int and boolean types. By mistake if we are trying to apply for any other type
then we will get Error.
Note: The most significant bit acts as sign bit. 0 value represents +ve number where as 1 represents -ve value. positive numbers will be repesented
directly in the memory where as -ve numbers will be represented indirectly in 2's complement form.

Python Logical Operators
Operator
and (AND)
or (OR)
not (NOT)
For boolean types behaviour:
and ==>If both arguments are True then only result is True or ====>If atleast one arugemnt is True then result is True not
==>complement
True and False ==>False
True or False ===>True
not False ==>True x and y: ==>if x is evaluates to false return x
otherwise return y .
Note = If first argument is zero then result is zero
otherwise result is y.
x or y: If x evaluates to True then result is x otherwise
result is y
not x:
If x is evalutates to False then result is True otherwise
False

Python Membership Operators
Operator
in
not in
We can use Membership operators to check whether the given object present in the given collection.(It may be String,List,Set,Tuple
or Dict)
in -Returns True if the given object present in the specified
Collection
not in -Retruns True if the given object not present in the specified Collection

Python Identity Operators
We can use identity operators for address comparison.
There are 2 identity operators are available
1. is
2. is not
r1 is r2 returns True if both r1 and r2 are pointing to the same object
r1 is not r2 returns True if both r1 and r2 are not pointing to the same object
We can use is operator for address comparison where as == operator for
content comparison.

Python Type Casting
int(value)
float(value)
str(value)
bin(value)
oct(value)
hex(value)
bool(value)
chr(value)
ord(value)
We can convert one type value to another type.
This conversion is called Typecasting or Type coersion.
Note:
• We can convert from any type to int except complex type.
• If we want to convert str type to int type, compulsary str
should contain only integral value and should be specified in base-10

Python Program to find Type and Address of a Value:

Operator Precedence
If multiple operators present then which operator will be evaluated first is decided
by operator precedence.

Math Module in Python
A Module is collection of functions, variables and classes etc.
Math is a module that contains several functions to perform mathematical operations
If we want to use any module in Python, first we have to import that module.

Conditional and Looping
Constructs

Decision Making
Decision-making is the anticipation of conditions occurring during the execution of a program
and specified actions taken according to the conditions.
if
if condition : statement
or
if condition :
statement-1
statement-2
statement-3
If condition is true then statements will be
executed.
if-else:
if condition :
Action-1
else :
Action-2
if condition is true then Action-1
will be executed otherwise
Action-2 will be executed.
if-elif-else:
if condition1:
Action-1
elif condition2:
Action-2
elif condition3:
Action-3
elif condition4:
Action-4 else:
Default Action
Based condition the
corresponding action
will be executed.

Code examples for If, else and elif

Nested-If Statement
We can use one if or else if statement inside another if or else if statement(s).
Else operator for Both condition Elif solve this problem

Relational Operator in Decision Making
Membership Operator in Decision Making

Identical Operator in Decision Making

Looping and Iteration
A loop statement allows us to execute a statement or group of statements multiple times. The following
diagram illustrates a loop statement
If we want to execute a group of statements multiple times
then we should go for Iterative statements.
1. for loop
2. while loop
If we want to execute some action for every element
present in some sequence(it may be string or
collection)then we should go for for loop.
where sequence can be string or any collection. Body will be
executed for every element present in the sequence.

While Loop
A while loop statement in Python programming language repeatedly executes a
target statement as long as a given condition is true. If we want to execute a group of statements
iteratively until some condition false,then we should go for while loop.

For Loop
It has the ability to iterate over the items of any sequence, such as a list or a string.
Range can accept 3 parameters like [range(1,10,2)] 1
is initial point, 10 is condition and 2 is step
Sometimes we can take a loop inside another loop,which
are also known as nested loops.

Nested Loops
Python allow nested looping
We can use loops to repeat code execution
Repeat code for every item in sequence ==>for loop
Repeat code as long as condition is true ==>while loop

Transfer Statements --- Break and Continue
Break -- We can use break statement inside loops to break loop execution based on some condition.
Continue -- We can use continue statement to skip current iteration and continue next iteration.

Loops with else block:
Insideloopexecution,ifbreakstatementnotexecuted,then
onlyelsepartwillbeexecuted.elsemeans loopwithoutbreak
Break and Continue

Count Number of Digits Using Loop
Prime Number Using Nested Loop

Find a Number is Palindrome or Not Find a Number is Armstrong or Not

Pass Statement
pass is a keyword in Python. In our programming syntactically if block is required which won't do anything then we
can define that empty block with pass keyword.
|- It is an empty statement
|- It is null statement
|- It won't do anything .
Sometimes in the parent class we have to declare a function with empty body and child class responsible to
provide proper implementation. Such type of empty body we can define by using pass keyword.

String
MANIPULATION AND OPERATIONS
STRING FUNCTIONS & PROBLEMS
The most commonly used object in any project and in any programming language is String only. Hence we should be
aware of complete information about String data type.
What is a String?
Any sequence of characters within either single quotes or double quotes is considered as a String.
Comparison of Strings:
We can use comparison operators (<,<=,>,>=) and equality operators(==,!=) for strings.
Comparison will be performed based on alphabetical order.

We can also use triple quotes to use single quotes or double quotes as symbol
inside String literal.
Eg:
S = 'This is ' single quote symbol' ==>invalid
S = 'This is ' single quote symbol' ==>valid
S = "This is ' single quote symbol"====>valid
S = 'This is " double quotes symbol' ==>valid
S ='The "Python Notes" by ‘Nishant' is very helpful' ==>invalid
S = "The "Python Notes" by ‘Nishant' is very helpful"==>invalid
S = 'The "Python Notes" by ‘Nishant' is very helpful' ==>valid
S = '''The "Python Notes" by ‘NIshant' is very helpful''' ==>valid
How to access characters of a String:
We can access characters of a string by using the following ways.
1. By using index 2. By using slice operator
Python supports both +ve and -ve index.
+ve index means left to right(Forward direction)
-ve index means right to left(Backward direction)
String and its Functions

We can use the following 4 methods
For forwarding direction:
• find() --Returns index of first occurrence of the given substring. If it is not available then we will get -1.
• index() -- index() method is exactly same as find() method except that if the specified substring is not available
then we will get ValueError.
For backward direction:
• rfind()
• rindex()
Finding Substrings:
s=input("Enter main string:")
subs=input("Enter sub string:") flag=False
pos=-1
n=len(s)
while True:
pos=s.find(subs,pos+1,n)
if pos==-1:
break
print("Found at position",pos)
flag=True
if flag==False:
print("Not Found")

startswith() and endswith()
To check type of characters present in a string:
Python contains the following methods for this purpose.
1) isalnum(): Returns True if all characters are alphanumeric( a to z , A to Z ,0
to9 )
2) isalpha(): Returns True if all characters are only alphabet symbols(a to
z,A to Z)
3) isdigit(): Returns True if all characters are digits only( 0 to 9)
4) islower(): Returns True if all characters are lower case alphabet symbols
5) isupper(): Returns True if all characters are upper case aplhabet
symbols
6) istitle(): Returns True if string is in title case
7) isspace(): Returns True if string contains only spaces

strip(), lstrip(), rstrip()min() and max() ,swapcase and split

Formatting the Strings:
We can format the strings with variable values by using replacement operator {} and format() method.

Program to calculate length of string
String code Example
Program to make a new string from 1st 2 and last 2
characters of a string

List
LISTS ARE ONE OF THE MOST POWERFUL TOOLS IN
PYTHON. THEY ARE JUST LIKE THE ARRAYS DECLARED
IN OTHER LANGUAGES. BUT THE MOST POWERFUL
THING IS THAT LIST NEED NOT BE ALWAYS
HOMOGENOUS.

Program to get the largest number from a list.
Program to get List from user

Program to count the number of strings where the string length is 2 or
more and the first and last character are same from a given list of strings.
List Code Examples
Program to remove duplicate values from list

Program to sorting a list Program to convert list to str

Tuple
A TUPLE IS ANOTHER SEQUENCE DATA TYPE THAT IS
SIMILAR TO THE LIST. A TUPLE CONSISTS OF A
NUMBER OF VALUES SEPARATED BY COMMAS. UNLIKE
LISTS, HOWEVER, TUPLES ARE ENCLOSED WITHIN
PARENTHESES.

Tuple manipulations and operations.
*Tuple is a immutable data type. So it does not support all the operations like list or
other muttable data types

Program to unpack a tuple in variables.

Program to create a tuple and sort it.
tup=()

Program to count element based on data type

Set
A SET CONTAINS AN UNORDERED COLLECTION OF
UNIQUE AND IMMUTABLE OBJECTS. THE SET DATA
TYPE IS, AS THE NAME IMPLIES, A PYTHON
IMPLEMENTATION OF THE SETS AS THEY ARE KNOWN
FROM MATHEMATICS.

Program to test whether every element in S is in T and every element in T is in S.

Program create a Shallow copy of a set

Program to find maximum and minimum value of set

Dictionary
IN PYTHON, THE DICTIONARY IS SIMILAR TO HASH OR
MAPS IN OTHER LANGUAGES. IT CONSISTS OF KEY-
VALUE PAIRS. THE VALUE CAN BE ACCESSED BY A
UNIQUE KEY IN THE DICTIONARY.

Program to concatenate dictionaries to form a new one

Program to generate and print a dictionary that contains a number (between 1 and n) in the form (x, x*x).

Program to map two lists into dictionary

Program to sort a dictionary by key

Test series
 PROGRAM TO COUNT OCCURRENCE OF A CHARACTER IN A STRING
 PROGRAM TO COUNT THE NUMBER OF STRINGS WHERE THE STRING
LENGTH IS 2 OR MORE AND THE FIRST AND LAST CHARACTER ARE SAME
FROM A GIVEN LIST OF STRINGS.
 PROGRAM TO COUNT ELEMENT OF DIFFERENT DATA TYPE
 PROGRAM TO CREATE A TUPLE AT RUN TIME VIA USER INPUT
 PROGRAM TO SHORT A TUPLE OF INTEGER ELEMENT VIA CODE

Functions in Python
If a group of statements is repeatedly required then it is not recommended to write these
statements everytime seperately.We have to define these statements as a single unit and we
can call that unit any number of times based on our requirement without rewriting. This unit
is nothing but function.
The main advantage of functions is code Reusability.
Note: In other languages functions are known as methods,procedures,subroutines etc .
Python supports 2 types of functions
1. Built in Functions 2. User Defined Functions

Functions and its Syntax
Note: While creating functions we
can use 2 keywords
1. def (mandatory)
2. return (optional)
Parameters
Parameters are inputs to the function. If a function contains parameters,then
at the time of calling,compulsory we should provide values
otherwise,otherwise we will get error.
Return Statement:-
Function can take input values as parameters and executes business logic, and
returns output to the caller with return statement.

Example for Return statement Returning multiple values from a function:
In other languages like C,C++ and Java, function can return
atmost one value. But in Python, a function can return any
number of values.

Arguments and Types of Functions:- 1 Positional Argument
These are the arguments passed to function in correct positional
order.
The number of arguments and position of arguments must be
matched. If we change the order then result may be changed.
If we change the number of arguments then we will get error.
Note  If three actual arguments given and there are
only two formal parameter allowed then it show an error

Default parameter function
Keyword Functions
We can pass argument values by keyword i.e by parameter
name
Here the order of arguments is not important but number of
arguments must be matched.
We can use both positional and keyword arguments
simultaneously. But first we have to take positional arguments
and then keyword arguments,otherwise we will get syntax
error.
Sometimes we can provide default values for
our positional arguments.
If we are not passing any name then only default value will
be considered.

Variable length parameter
1. * indicate that a variable can store multiple values
2. ** indicate that a variable can store multiple values with key
Note: We can mix variable length arguments with positional arguments.
After variable length argument,if we are taking any other arguments then we should provide
values as keyword arguments.
Sometimes we can pass variable number of arguments to our function,such type of
arguments are called variable length arguments.

Local and Global
Global Variables
The variables which are declared
outside of function are called global
variables.These variables can be
accessed in all functions of that
module.
Local Variables:
The variables which are declared inside a
function are called local variables. Local
variables are available only for the
function in which we declared it.i.e from
outside of function we cannot access.
Global keyword:
We use global keyword for the2 purposes:
1. To declare global variable inside function
2. To make global variable available to
the function so that we can perform
required modifications
NoteIf global variable and local variable having the same name
then we can access global variable inside a function as follows

Function Recurssive Calling
A function that calls itself is known as Recursive Function.The main advantages of recursive functions are:
1. We can reduce length of the code and improves readability
2. We can solve complex problems very easily.

Functions Anonymous
Sometimes we can declare a function without any name,such type of nameless functions are called anonymous functions or lambda
functions. The main purpose of anonymous function is just for instant use(i.e for one time usage).
lambda Function: -- By using Lambda Functions we can write very concise code so that readability of the program will be improved.
Lambda Function internally returns expression value and we are not required to write return statement explicitly.
Sometimes we can pass a function as an argument to another function. In such cases lambda functions are best choice.
filter() function:-- We can use filter() function to filter values from the given sequence based on some condition.
filter(function,sequence) where function argument is responsible to perform conditional check
sequence can be list or tuple or string.
map() function: --For every element present in the given sequence,apply some functionality and generate new
element with the required modification. For this requirement we should go for map() function.
Eg: For every element present in the list perform double and generate new list of doubles.
reduce() function:-- reduce() function reduces sequence of elements into a single element by applying
the specified function. reduce() function present in functools module and hence we should write import
statement.

Examples with Lambda, Map and Reduce
In Python every thing is treated as object.
Even functions also internally treated as
objects only.

Function insidefunction
Function Aliasing
For the existing function we can give another
name, which is nothing but function aliasing.
We can declare a function inside another function,
such type of functions are called Nested functions.

Closure function
If a function have an inner function and
return it then it is called closure.
Note: We can pass function as argument to
another function
Eg: filter(function,sequence)
map(function,sequence)
reduce(function,sequence)
Square of the elements

Multiply of all no. Of tuple
Reverse a string
Reverse Using Recursion

Calculate block & small letters
Find unique Elements from List

Reverse a number
Reverse a number using recursion

Function Decorators
Decorator is a function which can take a function as argument and extend its functionality and
returns modified function with extended functionality.
But we want to modify this function to provide different message if name is Sam. We can do this without touching wish()
function by using decorator.
@ is use to call
decorator function

More With Decorators
Using Decorator without @ With Condition

Decorator Chaining
We can define multiple decorators for the same function and all these decorators will form
Decorator Chaining.

Generators
Generator is a function which is responsible to generate a sequence of values. We can write generator
functions just like ordinary functions, but it uses yield keyword to return values.
Genrator with reverse ordering
Fibonacci with Python

More with Generators
Advantages of Generator Functions:
1. When compared with class level iterators, generators are very easy to use
2. Improves memory utilization and performance.
3. Generators are best suitable for reading data from large number of large files
4. Generators work great for web scraping and crawling.
Generators vs Normal Collections wrt Memory Utilization:
Normal Collection:
l=[x*x for x in range(10000000000000000)] print(l[0])
We will get MemoryError in this case because all these values are required to store in the memory.
Generators:
g=(x*x for x in range(10000000000000000)) print(next(g))
Output: 0 We won't get any MemoryError because the values won't be stored at the beginning

Procedural vs Modular
Programming
PROCEDURAL PROGRAMMING INVOLVES FOLLOWING AN ALGORITHM
OR A PROCEDURE TO IMPLEMENT ON YOUR SOFTWARE. THE NUMBER
CRUNCHING SOFTWARES ARE GENERALLY BASED ON PROCEDURAL
PROGRAMMING.
WHEREAS MODULAR PROGRAMMING INVOLVING DIVIDING YOUR
OBJECTIVE INTO MODULES AND THEN PIPELINING THE MODULES TO
OBTAIN THE DEFINED OUTPUT. MODULES ARE MADE ON THE BASIS OF
SIMILARITY BETWEEN THE FUNCTIONS.

Modules
A module is a file containing Python definitions and statements. A module can define functions, classes and variables. A module
can also include runnable code. Grouping related code into a module makes the code easier to understand and use.
A group of functions, variables and classes saved to a file, which is nothing but module. Every Python file (.py) acts as a module.
Creating any Module step by step:
1 Create a py file with functions and variables.
2 If we want to use members of module in our
program then we should import that module.
import modulename
3We can access members by using module name.
modulename.variable
modulename.function()
Note: whenever we are using a module in our program, for that module compiled file will be generated and stored in the hard disk
permanently.
from ... import:
We can import particular members of module by using from ... import . The main advantage of this is we can access members
directly without using module name.
We can import all members of a module as follows
from NIshant import *

Modules and More
Various possibilties of import:
• import modulename
• import module1,module2,module3
• import module1 as m
• import module1 as m1,module2 as m2,module3
• from module import member
• from module importmember1,member2,memebr3
• from module import memeber1 as x
• from module import *
Note  Once we defined as alias name,we should use alias
name only and we should not use original name.
Reloading a Module:
By default module will be loaded only once eventhough we
are importing multiple multiple times
test module will be loaded only once eventhough we are importing multiple times.
The problem in this approach is after loading a module if it is updated outside then updated version of module1 is
not available to our program.
We can solve this problem by reloading module explicitly based on our requirement. We can reload by using
reload() function of imp module.
The main advantage of explicit module reloading is we can ensure that updated version is always available to our program.
Finding members of module by using dir() function:
Python provides inbuilt function dir() to list out all members of current module or a specified module.
dir() ===>To list out all members of current module dir(moduleName)==>To list out all members of specified module

Built-in Modules
There is a wide range available of built-in modules in python.
The Special variable __name__:
For every Python program , a special variable __name__ will be added internally. This variable stores information
regarding whether the program is executed as an individual program or as a module.
If the program executed as an individual program then the value of this variable is __main__ If the program executed as a
module from some other program then the value of this variable is the name of module where it is defined.
Hence by using this __name__ variable we can identify whether the program executed directly or as a module.

More on Datetime Modules
Name and Main Concept

Working with Modules
There are so many modules present in python, like math module. Now we discuss random module.

Packages and its structure
Summary diagram of library,packages,modules which contains functions,classes and variables

All underscores in python
In python there are underscores act differently so we study all cases related to underscores.

OOPs in Python
OOPs (Object Oriented Programming) is basic concept of programming language which is widely
use in C++, PHP, ASP.net languages. It is Problem Solving Approach which is carried out using
Object. This is one of influential development used in computer Programming. Main Purpose of
Object Oriented Programming is to simplify a design, programming.
Why we use OPPs.
In Procedural Programming, Program is divided into small parts called Function. Most
of the variables are Global in nature which can be accessed freely from any function
and Data can flow from function to function because of which Data is not Secure
whereas in OOPs Data cannot Move easily from function to function it can make Data
secure using access specifier like Private and Protected because of which Data is
Secure as compare to Procedural Programming. Procedural Programming give the
importance to procedure instead of Data unlike OOPs give more preference to Data
in Place of Procedure.
There is one major exception to that statement. If you want to create a customized data type (such as a Complex or Fraction
number type), and then use it in multiple programs, OOP can be very helpful.
Looked at one way, OOP is actually the creation of customized data types, and therefore, in theory, can be useful even in very
simple environments.
Generally, though, OOP is most useful in one of two situations:
In very complex programs.
In applications that interact with a GUI, network, or event-based programming system.

Procedural vs OOPs
POPs OOPs
In POP, program is divided into small
parts called functions.
In OOP, program is divided into parts
called objects.
In POP, Importance is not given to
data but to functions as well as
sequence of actions to be done.
In OOP, Importance is given to the data
rather than procedures or functions
because it works as a real world.
POP does not have any access
specifier.
OOP has access specifiers named Public,
Private, Protected, etc.
POP does not have any proper way
for hiding data so it is less secure.
OOP provides Data Hiding so provides
more security.
In POP, Overloading is not possible. In OOP, overloading is possible in the form
of Function Overloading and Operator
Overloading.
What is an Object?
An object is nothing but a self-contained component
which consists of methods and properties to make a
particular type of data useful.
An object is a real world entity. Pysical existence of a
class is nothing but object. We can create any number of
objects for a class.
From a programming point of view, an object can be a
data structure, a variable or a function. It has a memory
location allocated.
The object is designed as class hierarchies.
An object contain two things attributes(data, property)
and behavior(task).
Example:= If Human is an object then Attributes are like
Name,height,weight,hobbies etc and Behaviours are
walk,talk,eat,sleep etc.
So as an object I know something and on the basis
of know something then I do something.

OOPs Concept
What is Class?
A class is a blueprint or prototype that defines the
variables and the methods (functions) common to all
objects of a certain kind. In Python every thing is an
object. To create objects we required some Model
or Plan or Blue print, which is nothing but class. We can
write a class to represent properties (attributes)
and actions (behaviour) of object. Properties can be
represented by variables. Actions can be represented
by Methods. Hence class contains both variables and
methods. Object is a instance of class.
1. Instance Methods
2. Class Methods
3. Static Methods

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Python ---Constructor
A constructor is a special type of method (function) which is used to initialize the instance
members of the class.
1) Constructor is used for Initializing the values to the data members of the Class.
1) Constructor is that whose name is same as name of class.
2) Constructor gets Automatically called when an object of class is created.
3) Constructors never have a Return Type even void.
4) Constructor are of Default(Non Parameterized), Parameterized and Copy Constructors.
2) Constructor is optional and if we are not providing any constructor then python will provide
default constructor.
3) Constructor definition is executed when we create the object of this class. Constructors also
verify that there are enough
resources for the object to perform any start-up task.
 Constructor is a special method in python.
 The name of the constructor should be __init__(self)
 Constructor will be executed automatically at the time of object creation.
 The main purpose of constructor is to declare and initialize instance variables.
 Per object constructor will be exeucted only once.
 Constructor can take atleast one argument(atleast self)
Heap
Memory
All objects
Address
In python, the method __init__ simulates the constructor of the class. This method is
called when the class is instantiated. We can pass any number of arguments at the time of
creating the class object, depending upon __init__ definition. It is mostly used to initialize
the class attributes. Every class must have a constructor, even if it simply relies on the
default constructor.

Along with the other attributes, a python class also contains some
built-in class attributes which provide information about the class.
Inbuilt Class Attrributes and Functions
SN Attribute Description
1 __dict__ It provides the
dictionary
containing the
information about
the class
namespace.
2 __doc__ It contains a string
which has the class
documentation
3 __name__ It is used to access
the class name.
4 __module__ It is used to access
the module in
which, this class is
defined.
5 __bases__ It contains a tuple
including all base
classes.
Inbuilt class functions--The in-built
functions defined in the class are
described in the following table
SN Function Description
1 getattr(obj,name,d
efault)
It is used to access
the attribute of the
object.
2 setattr(obj,
name,value)
It is used to set a
particular value to
the specific
attribute of an
object.
3 delattr(obj, name) It is used to delete
a specific attribute.
4 hasattr(obj, name) It returns true if
the object contains
some specific
attribute

Constructor vs Method
Types of Variables:
Inside Python class 3 types of variables are allowed.
1. Instance Variables (Object Level Variables)
2. Static Variables (Class Level Variables)
3. Local variables (Method Level Variables)
1. Instance Variables:
If the value of a variable is varied from object to object,
then such type of variables are called instance variables.
For every object a separate copy of instance variables will
be created.
Where we can declare Instance variables:
1. Inside Constructor by using self variable
2. Inside Instance Method by using self variable
3. Outside of the class by using object reference
variable
Class Variables

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Instance Variables(object level variable): -
1. Inside Constructor by using self variable: We can declare instance variables inside a constructor by using self keyword. Once
we creates object, automatically these variables will be added to the object.
2. Inside Instance Method by using self variable: We can also declare instance variables inside instance method by
using self variable. If any instance variable declared inside instance method, that instance variable will be
added once we call taht method.
3. Outside of the class by using object reference variable: We can also add instance variables outside of a class to
a particular object.
How to access Instance variables:
We can access instance variables with in the class by using self variable and outside of the class by using object reference.
How to delete instance variable from the object:
1. Within a class we can delete instance variable as follows
del self.variableName
2. From outside of class we can delete instance variables as follows
del objectreference.variableName
If we change the values of instance variables of one object then those changes won't be reflected to the remaining objects,
because for every object we are separate copy of instance variables are available.

Static Variable(Class Level Variable)
If the value of a variable is not varied from object to object, such type of variables we have to declare with
in the class directly but outside of methods. Such type of variables are called Static variables.
For total class only one copy of static variable will be created and shared by all objects of that class.
We can access static variables either by class name or by object reference. But recommended to use class
name.
If we change the value of static variable by using either self or object reference variable,then the value of static variable won't be
changed,just a new instance variable with thatname will be added to that particular object.

Local Variable
• Sometimes to meet temporary requirements of programmer,we can declare variables inside a method
directly,such type of variables are called local variable or temporary variables.
• Local variables will be created at the time of method execution and destroyed once method completes.
• Local variables of a method cannot be accessed from outside of method.

Method and its working
Types of Methods:
Inside Python class 3 types of methods are allowed . Instance Methods , Class Methods and Static Methods
1. Instance Methods: Inside method implementation if we are using instance variables then such type of
methods are called instance methods. Inside instance method declaration,we have to pass self variable.
2. Class Methods:
Inside method implementation if we are using only class
variables (static variables), then such type of methods we
should declare as class method.
We can declare class method explicitly by using
@classmethod decorator. For class method we should
provide cls variable at the time of declaration.
We can call classmethod by using classname or object
reference variable.

ClassMethod--The @classmethod decorator, is a builtin function decorator that is an expression that gets evaluated
after your function is defined. The result of that evaluation shadows your function definition.
A class method receives the class as implicit first argument, just like an instance method receives the instance.
A class method is a method which is bound to the class and not the object of the class.
They have the access to the state of the class as it takes a class parameter that points to the class and not the object
instance.
It can modify a class state that would apply across all the instances of the class. For example it can modify a class
variable that will be applicable to all the instances.
Static Method-- A static method does not receive an implicit first argument.
A static method is also a method which is bound to the class and not the object of the class.
A static method can’t access or modify class state.
It is present in a class because it makes sense for the method to be present in class.
Class Method Vs Static Method
A class method takes cls as first parameter while a static method needs no specific parameters.
A class method can access or modify class state while a static method can’t access or modify it.
In general, static methods know nothing about class state. They are utility type methods that take some parameters and
work upon those parameters. On the other hand class methods must have class as parameter.
We use @classmethod decorator in python to create a class method and we use @staticmethod decorator to create a
static method in python.
Class Method and Static Method

Static Method
In general these methods are general utility methods. Inside these methods we won't use
any instance or class variables.
Here we won't provide self or cls arguments at the time of declaration.
We can declare static method explicitly by using @staticmethod decorator.
We can access static methods by using classname or object reference.
Note: In general we can use only instance and static methods.Inside static method we can
access
• class level variables by using class name.
• class methods are most rarely used methods in python.

OOPs Concepts --- Polymorphism
Poly means many. Morphs means forms. Polymorphism means 'Many Forms'.
Polymorphism means same name with different forms(behaviour). E.g. Mobile.
Now there are various division for Polymorphism.
Polymorphism:
• Overloading
• Operator Overloading.
• Method Overloading.
• Constructor Overloading.
• Overriding
• Method Overriding.
• Constructor Overriding.

Overloading and its Types
In Overloading, there is a method, operator and constructor with same name but act differently in
multiple situation.
Example:-- If Bank is a class, deposit and withdrawal is a entity so there are multiple ways to
perform it like cash,
Check and DD etc.
So, In simple way same name with different arguments.
1. Operator Overloading: In Java It never exist.
2. In Python, we achieve Operator Overloading easily.e.g. 6+3, “a”+”b”, 9*2 and “n”*23.
3. It always achieve by using magic(Dunder ) function. And every operator in python has magic
method. And return
type of every magic method is output.

Method and Constructure Overloading(Early /Compile Time Binding)
If 2 methods having same name but different type of arguments then those methods are said to be overloaded methods.
Note: In python, there is no need to define type for anyone explicitly
so how overloading is not available in python.
Basically, in Python overloading concept is not required.
So, we not worry about different types of argments we worry about ,to pass number of arguments.
So for this we have, Default Arguments and Variable length arguments. We also perform overloading with constructors.
Method Overriding(Late/RunTime Binding):
What ever members available in the parent class are by default available to the child class through inheritance. If the child class
not satisfied with parent class implementation then child class is allowed to redefine that method in the child class based on its
requirement. This concept is called overriding. Overriding concept applicable for both methods and constructors.
Method overriding is a concept of object oriented programming that allows us to change the implementation of a function in
the child class that is defined in the parent class. It is the ability of a child class to change the implementation of any method
which is already provided by one of its parent class(ancestors).
Following conditions must be met for overriding a function:
Inheritance should be there. Function overriding cannot be done within a class. We need to derive a child class from a parent
class.
The function that is redefined in the child class should have the same signature as in the parent class i.e. same number of
parameters.

What is inheritance?
Inheritance is used to extend of parent class to its child class. Python can support single level,
multi level, hierarchal and multiple inheritance.

Inheritance in Python
Single Level Inheritance
• Single Parent and Single child
Multi level Inheritance
• One parent but multiple child at diff.
level.
Heirarical Inheritance
• One Parent but multiple child at same
level.
Multiple Inheritance
• MultipleParents but one single child.
At a fairly abstract level, super() provides the
access to those methods of the super-class (parent
class) which have been overridden in a sub-class
(child class) that inherits from it. With the help of
super(), from child class we can call parent class
members. The main motive of super is code
reusability.
Notes: From child class, by using super we cannot call
parent class instance variable we should use self only.
From child class by using super(), we can call parent class
static variable.
Hybrid Inheritance --- (Single + Multiple + Multilevel+Heirarical)
So for this there is a concept of MRO(Method Resolution Order)
• If we have Parent class and child class with same method name.
• So, When we call object then always first method excecute which
present in child and if not present in child then go to parent class.
• For A-- (A- obj)
• For B-- (B-A-obj)
• For C-- (C-A-obj)
• For D– (D-C-B-A-obj)

C3 Algo -- MRO
obj
B
A C
X Y
P
mro(P) = P,X,Y,C,A,B,O
So,here we see that mro for P not actually right.Due to hybrid
Inheritance and there is multiple level present so here for
Calculating MRO we use C3 Algorithm.
Mro(P) = [class(P) + merge(mro(Parents) at samelevel),parentlist]
Mro(P) = P+Merge(mro(x),mro(y),mro(c),XYC). 1 E.g.
Mro(P) = P+Merge(XABo,YBCo,Co,XYC).  step2.
Now here, first level is done now move toward next level.
For this we have to know about head and tail.
e.g.– If we have a list like ABCDEF so in this.
Head --- A
Tail --- BCDEF
For next level always remember one statement.
Mro(P) = P+X+Merge(ABo,YBCo,Co,YC).  step3. remove X
Mro(P) = P+X+A+Merge(Bo,YBCo,Co,YC).  step4. remove A
Now For B, So B is present in head and tail both then leave that list.
Mro(P) = P+X+A+Y+Merge(Bo,BCo,Co,C).  step5. remove Y
Mro(P) = P+X+A+Y+B+Merge(o,Co,Co,C).  step6. remove B
Mro(P) = P+X+A+Y+B+C+Merge(o,o,o).  step7 . remove C

Program to convert integer to roman

Program to convert roman to integer

Program to make possible unique subset

Program to find a pair of elements (indices of the two numbers)
from a given array whose sum equals a specific target number.

Python program to find the three elements that sum to zero from a set
(array) of n real numbers.

Program to implement pow(x, n).

Accessing parent constructor using super()

Passing values to parent constructor using base class name

File Handling
Python too supports file handling and allows users to handle files i.e., to read and write files, along with
many other file handling options, to operate on files.Python treats file differently as text or binary and this is
important. Each line of code includes a sequence of characters and they form text file.
As the part of programming requirement, we have to store our data permanently for future purpose. For
this requirement we should go for files.
Files are very common permanent storage areas to store our data.
And for Temporary storage we use List,Tuple and Dictionary etc. (Heap)
So Permanent storage are Files and Database.(Memory).
Types of Files:
There are 2 types of files
1. Text Files: Usually we can use text files to store character data eg: abc.txt
2. Binary Files: Usually we can use binary files to store binary data like
images,video files, audio files etc.

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File Handling
Opening a File:
Before performing any operation (like read or write) on the file,first we have to open that file.For this we should use Python's inbuilt
function open() .But at the time of open, we have to specify mode,which represents the purpose of opening file. e.g. f =
open(filename, mode)
The allowed modes in Python are
1. r open an existing file for read operation. The file pointer is positioned at the beginning of the file.If the specified file
does not exist then we will get FileNotFoundError.This is default mode.
2. w open an existing file for write operation. If the file already contains some data then it will be overridden. If the
specified file is not already avaialble then this mode will create that file.
3. a  open an existing file for append operation. It won't override existing data.If the specified file is not already avaialble
then this mode will create a new file.
4. r+  To read and write data into the file. The previous data in the file will not be deleted.The file pointer is placed at the
beginning of the file.
5. w+  To write and read data. It will override existing data.
6. a+ To append and read data from the file.It wont override existing data.
7. x  To open a file in exclusive creation mode for write operation. If the file already exists then we will get
FileExistsError.
Note: All the above modes are applicable for text files. If the above modes suffixed with 'b' then these represents for binary files. Eg: rb,wb,ab,r+b,w+b,a+b,xb

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File Handling
Closing a File:
After completing our operations on the file,it is highly recommended to close the file. For this we have to use close()
function. f.close()
Various properties of File Object:
Once we opend a file and we got file object,we can get various details related to that file by using its properties.
name Name of opened file
mode Mode in which the file is opened
closed  Returns boolean value indicates that file is closed or not
readable() Returns boolean value indicates that whether file is readable or not
writable()Returns boolean value indicates that whether file is writable or not.
Writing data to text files:
We can write character data to the text files by using the following 2 methods.
• write(str) -- while writing data by using write() methods, compulsory we have to provide line
seperator(n),otherwise total data should be written to a single line.
• writelines(list of lines)
Reading Character Data from text files:
We can read character data from text file by using the following read methods.
read() To read total data from the file.
read(n)To read 'n' characters from the file
readline() To read only one line
readlines()To read all lines into a list
The with statement:
The with statement can be used while opening a file.We can use this to group
file operation statements within a block. The advantage of with statement is it
will take care closing of file,after completing all operations automatically even
in the case of exceptions also, and we are not required to close explicitly.

28/07/2022
File Handling Operations
tell() We can use tell() method to return current position of the cursor(file pointer) from beginning of the file.
The position(index) of first character in files is zero just like string index.
Seek():We can use seek() method to move cursor(file pointer) to specified location. E.g.f.seek(offset, fromwhere)
offset represents the number of positions .
The allowed values for second attribute(from where) are
0---->From beginning of file(default value)
1---->From current position
2--->From end of the file # Note: Python 2 supports all 3 values but Python 3 supports only zero.
How to check a particular file exists or not?
We can use os library to get information about files in our computer. os module has path sub module,which contains isFile() function to check whether a
particular file exists or not? os.path.isfile(fname).
Handling csv files: CSV==>Comma seperated values
As the part of programming,it is very common requirement to write and read data wrt csv files. Python provides csv module to handle csv files.
Zipping and Unzipping Files:
It is very common requirement to zip and unzip files. The main advantages are:
1. To improve memory utilization
2. We can reduce transport time
3. We can improve performance.
To perform zip and unzip operations, Python contains one in-bulit module zip file. This module contains a class : ZipFile
OS Module for File Handling.

FileHandling Directory Working
It is very common requirement to perform operations for directories like
1. To know current working directory.
2. To create a new directory.
3. To remove an existing directory.
4. To rename a directory.
5. To list contents of the directory etc.
os.walk(path,topdown=True,onerror=None,followlinks=False)
It returns an Iterator object whose contents can be displayed by using for loop
path-->Directory path. cwd means .
topdown=True --->Travel from top to bottom
onerror=None --->on error detected which function has to execute.
followlinks=True -->To visit directories pointed by symbolic links.
Note: To display contents of particular directory,we have to provide that directory name as argument to walk() function.
os.walk("directoryname")
What is the difference between listdir() and walk() functions?
In the case of listdir(), we will get contents of specified directory but not sub directory contents. But in the case of walk() function we will get
contents of specified directory and its sub directories also.
Running Other programs from Python program:
os module contains system() function to run programs and commands. It is exactly same as system() function in C language.
os.system("commad string") The argument is any command which is executing from DOS.
OS To perform these operations,Python provides inbuilt
module os,which contains several functions to perform
directory related operations.
The above program display contents of current working
directory but not contents of sub directories.
If we want the contents of a directory including sub
directories then we should go for walk() function.

Program to create or open a
file.
OS Stats

Pickling and Unpickling the object
Sometimes we have to write total state of object to the file and
we have to read total object from the file.
The process of writing state of object to the file is called
pickling and the process of reading state of an object from the
file is called unpickling.
We can implement pickling and unpickling by using pickle
module of Python.
pickle module contains dump() function to perform pickling.
pickle.dump(object,file)
pickle module contains load() function to perform unpickling
obj=pickle.load(file)

Program to write multiple lines in a file

File seeking program to point a cusrsor on a specific charactor

Program to remove ‘n’ charactor

Program to copy content of a file in another file

Task: Write a program to create your profile in a text file
Your name, address, contact no, dob, father’s name, mother’s name, course, branch, year,
semester
 All information should be input at runtime by user
 All information should be in well format
 All information should be display immediately after writing
 File name should be entered by user at runtime
 File extension is your own choice

Exceptions Handling
IN ANY PROGRAMMING LANGUAGE THERE ARE 2 TYPES OF ERRORS ARE POSS IBLE.
1. SYNTAX ERRORS THE ERRORS WHICH OCCURS BECAUSE OF INVALID SYNTAX
ARE CALLED SYNTAX ERRORS
2. RUNTIME ERRORS  ALSO KNOWN AS EXCEPTIONS. WHILE EXECUTING THE PROGRAM IF
SOMETHING GOES WRONG BECAUSE OF END USER INPUT OR PROGRAMMING LO GIC OR MEMORY
PROBLEMS ETC THEN WE WILL GET RUNTIME ERRORS. EG: PRINT(10/0) ==>ZERODIVISIONERROR :
DIVISION BY ZERO.
N O T E : E X C E P T IO N H A N D LIN G C O N C E P T A P P LIC A B LE F O R R U N T IM E E R R O R S B U T N O T F O R S Y N TA X E R R O R S
WHAT IS EXCEPTION?
AN UNWANTED AND UNEXPECTED EVENT THAT DISTURBS NORMAL FLOW OF PR OGRAM IS CALLED
EXCEPTION.
THE MAIN OBJECTIVE OF EXCEPTION HANDLING IS GRACEFUL TERMINATIO N OF THE PROGRAM. EXCEPTION
HANDLING DOES NOT MEAN REPAIRING EXCEPTION. WE HAVE TO DEFINE ALTERNATIVE WAY TO CONTINUE
REST OF THE PROGRAM NORMALLY.

Default Exception Handing in Python:
Every exception in Python is an object. For every exception type the corresponding classes are available.
Whevever an exception occurs PVM will create the corresponding exception object and will check for handling code. If
handling code is not available then Python interpreter terminates the program abnormally and prints corresponding
exception information to the console. The rest of the program won't be executed.
Every Exception in Python is a class. All exception classes are child classes of BaseException.i.e every exception class
extends BaseException either directly or indirectly. Hence BaseException acts as root for Python Exception Hierarchy.
Customized Exception Handling by using try-except:
It is highly recommended to handle exceptions. The code which may raise exception is called risky code and we have to
take risky code inside try block. The corresponding handling code we have to take inside except block.
1. within the try block if anywhere exception raised then rest of the try block wont be executed eventhough we handled
that exception. Hence we have to take only risky code inside try block and length of the try block should be as less as
possible.
2. In addition to try block,there may be a chance of raising exceptions inside except and finally blocks also.
3. If any statement which is not part of try block raises an exception then it is always abnormal termination.

Control Flow of try and execpt

Try with multiple catch
The way of handling exception is varied from exception to exception. Hence for every exception type a
seperate except block we have to provide. i.e try with multiple except blocks is possible and recommended
to use.
If try with multiple except blocks available then based on raised exception the corresponding except block
will be executed.
If try with multiple except blocks available then the order of these except blocks is important .Python
interpreter will always consider from top to bottom until matched except block identified.
Single except block that can handle multiple exceptions:
We can write a single except block that can handle multiple different types of exceptions.
except (Exception1,Exception2,exception3,..): or except (Exception1,Exception2,exception3,..) as msg :
Parenthesis are mandatory and this group of exceptions internally considered as tuple.
Default except block:
We can use default except block to handle any type of exceptions. In default except block generally we can print
normal error messages.
***Note: If try with multiple except blocks available then default except block should be last,otherwise we will get
SyntaxError.

Finally block
1. It is not recommended to maintain clean up code(Resource Deallocating Code or Resource Releasing
code) inside try
block because there is no guarentee for the execution of every statement inside try block always.
2. It is not recommended to maintain clean up code inside except block, because if there is no exception
then except block
won't be executed.
Hence we required some place to maintain clean up code which should be executed always irrespective of
whether exception raised or not raised and whether exception handled or not handled. Such type of best
place is nothing but finally block.
The speciality of finally block is it will be executed always whether exception raised or not raised and
whether exception handled or not handled.
*** Note: There is only one situation where finally block won't be executed ie whenever we are using
os._exit(0) function.
Whenever we are using os._exit(0) function then Python Virtual Machine itself will be shutdown.In this
particular case finally won't be executed.

Finally Control Flow
Nested Block

else block with try-except-finally:
We can use else block with try-except-finally blocks. else block will be executed if and only if there are no exceptions inside
try block.
Without catch block else not working PVM not consider it.

Combination of try-except and Finally

Combination of Try-except-else-finally

User defined Exception
Types of Exceptions: 1. Predefined Exceptions 2. User Definded Exceptions
1. Predefined Exceptions:
Also known as in-built exceptions
The exceptions which are raised automatically by Python virtual machine whenver a particular event occurs, are called pre defined exceptions. Eg 1: Whenev
we are trying to perform Division by zero, automatically Python will raise ZeroDivisionError. print(10/0) Eg 2: Whenever we are trying to convert input
value to int type and if input value is not int value then Python will raise ValueError automatically.
x=int("ten")===>ValueError
2. User Defined Exceptions:
Also known as Customized Exceptions or Programatic Exceptions
Some time we have to define and raise exceptions explicitly to indicate that something goes wrong ,such type of exceptions are called User Defined Exceptio
or Customized Exceptions
Programmer is responsible to define these exceptions and Python not having any idea about these. Hence we have to raise explicitly based on our requiremen
using "raise" keyword.
Eg: InSufficientFundsException , InvalidInputException ,TooYoungException ,TooOldException.
How to Define and Raise Customized Exceptions:
Every exception in Python is a class that extends Exception class either directly or indirectly.
Syntax: class classname(predefined exception class name):
def __init__(self,arg):
self.msg=arg

Communication with
Network Server

An overview to Protocols and Ports
HTTP, SMTP, IMAP, FTP are high level protocols which are working on TCP and UDP
TCP and UDP are low level protocols
UDP use in video streaming, VOIP and Online games
HTTP
Web Server
SMTP & IMAP
Email Server
FTP
File Server
VOIP - Voice over internet protocol
UDP – User datagram protocol
IMAP – Internet message access protocol

Tkinter Widgets
Widgets Description
Button The Button widget is used to display buttons in your application
Canvas The Canvas widget is used to draw shapes, such as lines, ovals,
polygons and rectangles, in your application.
Checkbutton The Checkbutton widget is used to display a number of options as
checkboxes. The user can select multiple options at a time.
Entry The Entry widget is used to display a single-line text field for
accepting values from a user.
Frame The Frame widget is used as a container widget to organize other
widgets.
Label The Label widget is used to provide a single-line caption for other
widgets. It can also contain images.
Listbox The Listbox widget is used to provide a list of options to a user.
Menu The Menu widget is used to provide various commands to a user.
These commands are contained inside Menubutton.

Tkinter Widgets
Widgets Description
Message The Message widget is used to display multiline text fields for
accepting values from a user.
Radiobutton The Radiobutton widget is used to display a number of options as
radio buttons.
Text The Text widget is used to display text in multiple lines.
tkMessageBox This module is used to display message boxes in your applications.

Creating a tkinter entry with label widget

Task- Creating a login screen using tkinter

Creating radio button and check boxes

Display values from Radio Button and Check box

python ppt | Python Course In Ghaziabad | Scode Network Institute

Display values from Entry box on labels

Getting Values from Option Menu

Creating Dynamic Tkinter Widgets

Creating Button with Image + Text

Creating Listbox With Scroll Bar

Database in
Python
PLAY WITH SQLITE DATABASE
 CREATING & CONNECTING DB
 CREATING TABLES
 INSERTION, DELETION, UPDATION AND FETCHING RECORD.

Database Connectivity
Storage Areas As the Part of our Applications, we required to store our Data like Customers Information, Billing
Information, Calls Information etc.To store this Data, we required Storage Areas. There are 2 types of Storage Areas.
1) Temporary Storage Areas 2) Permanent Storage Areas
1.Temporary Storage Areas:
These are the Memory Areas where Data will be stored temporarily. Eg: Python objects like List, Tuple, Dictionary.
Once Python program completes its execution then these objects will be destroyed automatically and data will be
lost. 2.
2.Permanent Storage Areas:
Also known as Persistent Storage Areas. Here we can store Data permanently. Eg: File Systems, Databases, Data
warehouses,
Big Data Technologies etc
File Systems:
File Systems can be provided by Local operating System. File Systems are best suitable to store very less Amount of
Information.
Limitations:
1) We cannot store huge Amount of Information.
2) There is no Query Language support and hence operations will become very complex.
3) There is no Security for Data.
4) There is no Mechanism to prevent duplicate Data. Hence there may be a chance of Data Inconsistency Problems.
To overcome the above Problems of File Systems, we should go for Databases.

Python DataBase
Databases:
1) We can store Huge Amount of Information in the Databases.
2) Query Language Support is available for every Database and hence we can perform Database Operations very easily.
3) To access Data present in the Database, compulsory username and pwd must be required. Hence Data is secured.
4) Inside Database Data will be stored in the form of Tables. While developing Database Table Schemas, Database Admin
follow various Normalization Techniques and can implement various Constraints like Unique Key Constrains, Primary Key
Constraints etc which prevent Data Duplication. Hence there is no chance of Data Inconsistency Problems.
Limitations of Databases:
1) Database cannot hold very Huge Amount of Information like Terabytes of Data.
2) Database can provide support only for Structured Data (Tabular Data OR Relational Data) and cannot provide support for
Semi Structured Data (like XML Files) and Unstructured Data (like Video Files, Audio Files, Images etc)
To overcome these Problems we should go for more Advanced Storage Areas like Big Data Technologies, Data warehouses etc.
Note: The following is the list of all important methods which can be used for python database programming.
connect() cursor() execute() executescript() executemany() commit() rollback() fetchone() fetchall() fetchmany(n) fetch() close()

Creating and Connecting with DB

Update and delete record from table
Output will appear after
executing fetch command

Threading in
Python
 THREAD
 MULTI THREADING

What is a Thread?
A thread is an entity within a process that can be scheduled for execution. Also, it is the smallest unit of
processing that can be performed in an OS. It is also consider as independent part of a process. Also called flow
of executuion.
A thread contains all this information in a Thread Control Block (TCB):
Threading and its Concept
What is MultiThreading?
It is the concept, which is used by operating system to perform the Multi Tasking within the system.
Multi Tasking means executing several task simultaneously. In this, there are two types of Multi Tasking present.
1. Process based Multi Tasking. 2. Thread based Multi Tasking.
Multithreading is defined as the
ability of a processor to execute
multiple threads concurrently.
Example related to multi tasking like at same
time students concentrate on lectures and also
operates its mobile and also look here and
there.

Types of Multi Threading
1. Process based Multi Tasking:
Executing several tasks simmultaneously where each task is a seperate independent process is called process based multi tasking. In this,
all tasks entirely differen from each other means there is no relation between them. It is very much suitable as OS level. And also appear
for application level sometimes.
Eg: while typing python program in the editor we can listen mp3 audio songs from the same system. At the same time we can download a
file from the internet. All these taks are executing simultaneously and independent of each other. Hence it is process based multi
tasking.
2. Thread based MultiTasking:
Executing several tasks simultaneously where each task is a seperate independent part of the same program, is called Thread based multi
tasking, and each independent part is called a Thread. In this, every part is different but belong towards one program.
Note: Whether it is process based or thread based, the main advantage of multi tasking is to improve performance of the system
by reducing response time.
The main important application areas of multi threading are:
1. To implement Multimedia graphics , 2. To develop animations ,3. To develop games, 4. To develop web and appln servers.
Everytime we try to execute bulk instructions simultaneously,not one by one. Python provides one inbuilt module "threading" to provide
support for developing threads. Hence developing multi threaded Programs is very easy in python.
Every Python Program by default contains one thread which is nothing but MainThread.

Thread Creation
The ways of Creating Thread in Python:
We can create a thread in Python by using 3 ways :
1. Creating a Thread without using any class(Functional way).
2. Creating a Thread by extending Thread class(OOP).
3. Creating a Thread without extending Thread class(OOP).
Note:Thread is a pre defined class present in threading module which can be used to create our own Threads.
Main thread is responsible to create and start child thread. Once child started then both act independently.
Setting and Getting Name of a Thread:
Every thread in python has name. It may be default name generated by Python or Customized Name provided by
programmer. We can get and set name of thread by using the following Thread class methods.
t.getName() ,t.name----------Returns Name of Thread.
t.setName(newName) ,t.name = “xyz”-- To set our own name.
Note: Every Thread has implicit variable "name" to represent name of Thread.
• Thread Identification Number(ident): For every thread internally a unique identification number is available.
• active_count(): This function returns the number of active threads currently running.
• enumerate() function: This function returns a list of all active threads currently running.
• isAlive(): method checks whether a thread is still executing or not.
• join() method: If a thread wants to wait until completing some other thread then we should go for join() method.e..gparty

28/07/2022
Multi ThreadingThread Control Block (TCB)
Thread Identifier: Unique id (TID) is assigned to every new thread.
Stack pointer: Points to thread’s stack in the process. Stack contains the local variables under thread’s scope.
Program counter: A register which stores the address of the instruction currently being executed by thread.
Thread state: can be running, ready, waiting, start or done.
Thread’s register set: registers assigned to thread for computations.
Parent process Pointer: A pointer to the Process control block (PCB) of the process that the thread lives on.
Daemon Threads:
The threads which are running in the background are called Daemon Threads. The main objective of Daemon Threads
is to provide support for Non Daemon Threads( like main thread).e.g. Garbage Collection.
Whenever Main Thread runs with low memory, immediately PVM runs Garbage Collector to destroy useless objects
and to provide free memory,so that Main Thread can continue its execution without having any memory problems.
We can check whether thread is Daemon or not by using t.isDaemon() method of Thread class or by using daemon
property.
Nature of Daemon Thread--We can change Daemon nature by using setDaemon() method of Thread class.
t.setDaemon(True) But we can use this method before starting of Thread.i.e once thread started,we cannot change its
Daemon nature,otherwise we will get RuntimeException:cannot set daemon status of active thread.
Default Nature:
By default Main Thread is always non-daemon.But for the remaining threads Daemon nature will be inherited from
parent to child.i.e if the Parent Thread is Daemon then child thread is also Daemon and if the Parent Thread is Non
Daemon then ChildThread is also Non Daemon. But if we want to make child opposite to parent it possible

28/07/2022
Synchronization with Threads
If multiple threads are executing simultaneously then there may be a chance of data inconsistency problems.
Thread synchronization is defined as a mechanism which ensures that two or more concurrent threads do not
simultaneously execute some particular program segment known as critical section.
Critical section refers to the parts of the program where the shared resource is accessed.
Synchronization means at a time only one Thread
The main application areas of synchronization are
1. Online Reservation system 2. Funds Transfer from joint accounts etc
In Python, we can implement synchronization by using the following
1. Lock 2. RLock 3. Semaphore
Concurrent accesses to shared resource can lead to race condition.
A race condition occurs when two or more threads can access shared data and they try to change it at the same time.
As a result, the values of variables may be unpredictable and vary depending on the timings of context switches of
the processes.
Synchronization By using Lock concept:
Locks are the most fundamental synchronization mechanism provided by threading module. We can create Lock
object as follows l=Lock()
The Lock object can be hold by only one thread at a time.If any other thread required the same lock then it will wait
until thread releases lock.(similar to common wash rooms,public telephone booth etc)
A Thread can acquire the lock by using acquire() method. l.acquire() and using release() method. l.release()
Note: To call release() method compulsory thread should be owner of that lock.i.e thread should has the lock
already,otherwise we will get Runtime Exception saying .

28/07/2022
Synchronization with threads
Problem with Simple Lock:
The standard Lock object does not care which thread is currently holding that lock.If the lock is held and any thread attempts
to acquire lock, then it will be blocked,even the same thread is already holding that lock.
If the Thread calls recursive functions or nested access to resources,then the thread may trying to acquire the same lock again
and again,which may block our thread.
RLOCK
To overcome this problem, we should go for RLock(Reentrant Lock). Reentrant means the thread can acquire the same lock
again and again.If the lock is held by other threads then only the thread will be blocked. Reentrant facility is available only
for owner thread but not for other threads.
This RLock keeps track of recursion level and hence for every acquire() call compulsory release() call should be available. i.e
the number of acquire() calls and release() calls should be matched then only lock will be released.
1. Only owner thread can acquire the lock multiple times
2. The number of acquire() calls and release() calls should be matched.
Difference between Lock and RLock
Lock:
1. Lock object can be acquired by only one thread at a time.Even owner thread also cannot acquire multiple times. 2. Not
suitable to execute recursive functions and nested access calls 3. In this case Lock object will takes care only Locked or
unlocked and it never takes care about owner thread and recursion level.
RLock:
1. RLock object can be acquired by only one thread at a time, but owner thread can acquire same lock object multiple times.
2. Best suitable to execute recursive functions and nested access calls 3. In this case RLock object will takes care whether
Locked or unlocked and owner thread information, recursiion level.

Synchronization with Lock
Locks are the most fundamental synchronization mechanism provided by threading module. We can create
Lock object as follows l=Lock()
The Lock object can be hold by only one thread at a time.If any other thread required the same lock then it
will wait until thread releases lock.(e.g==public property)
A Thread can acquire the lock by using acquire() method.==== l.acquire()
A Thread can release the lock by using release() method. ==== l.release()
Note: To call release() method compulsory thread should be owner of that lock.i.e thread should has the lock
already,otherwise we will get Runtime Exception saying RuntimeError: release unlocked lock

Character classes: We can use character classes to search a group of
characters
1. [abc]===>Either a or b or c
2. [âbc] ===>Except a and b and c
3. [a-z]==>Any Lower case alphabet symbol
4. [A-Z]===>Any upper case alphabet symbol
5. [a-zA-Z]==>Any alphabet symbol
6. [0-9] Any digit from 0 to 9
7. [a-zA-Z0-9]==>Any alphanumeric character
8. [â-zA-Z0-9]==>Except alphanumeric characters(Special Characters)
Regular Expression
Pre defined Character classes:
• s --Space character
• S --Any character except space character
• d --Any digit from 0 to 9
• D --Any character except digit
• w --Any word character [a-zA-Z0-9]
• W --Any character except word character (Special Characters) [â-zA-Z0-9].
• “.” --Any character including special characters
Qunatifiers: Means Quantity
We can use quantifiers to specify the number of
occurrences to match.
a Exactly one 'a'
a+ Atleast one 'a'
a* Any number of a's including zero number
a? Atmost one 'a' ie either zero number or one no.
a{m} Exactly m number of a's
a{m,n} Min m number of a's and Max n no. of a's
^x It will check whether target string starts with x or not
x$ It will check whether target string ends with x or not

28/07/2022
Regular Expression-Introduction
Regular expression is a sequence of character(s) mainly used to find and replace patterns in a string or file. Regular expressions
(called REs, or regexes, or regex patterns) are essentially a tiny, highly specialized programming language embedded inside Python
and made available through the re module. Using this little language, you specify the rules for the set of possible strings that you
want to match; this set might contain English sentences, or e-mail addresses, or anything you like.
If we want to represent a group of Strings according to a particular format/pattern then we should go for Regular Expressions. i.e
Regualr Expressions is a declarative mechanism to represent a group of Strings accroding to particular format/pattern.
Regular expressions use two types of characters:
a) Meta characters: As the name suggests, these characters have a special meaning, similar to * in wild card.
e.g. -- . ^ $ * + ? { } [ ] | ( )
b) Literals (like a,b,1,2…)
In Python, we have module “re” that helps with regular expressions. So you need to import library re before you can use regular
expressions in Python.
Applications
1. To develop validation frameworks/validation logic
2. To develop Pattern matching applications (ctrl-f in windows, grep in UNIX etc)
3. To develop Translators like compilers, interpreters etc
4. To develop digital circuits
5. To develop communication protocols like TCP/IP, UDP etc.
Functions-----
1. compile() re module contains compile() function to compile a pattern into RegexObject.
2. finditer(): Returns an Iterator object which yields Match object for every Match.
start()--Returns start index of the match 2. end()--Returns end+1 index of the match 3. group()--Returns the matched string

28/07/2022
Regular Expression-Functions
Methods of Regular Expressions?
The ‘re’ package provides multiple methods to perform queries on an input string. Here are the most commonly used methods,
• re.match()---We can use match function to check the given pattern at beginning of target string. If the match is available
then we will get Match object, otherwise we will get None.
• re.fullmatch()---We can use fullmatch() function to match a pattern to all of target string. i.e complete string should be
matched according to given pattern. If complete string matched then this function returns Match object
otherwise it returns None.
• re.search()--- We can use search() function to search the given pattern in the target string. If the match is available then it
returns the Match object which represents first occurrence of the match. If the match is not available then it
returns None
• re.findall()---To find all occurrences of the match. This function returns a list object which contains all occurrences.
• re.split()--- If we want to split the given target string according to a particular pattern then we should go for split() function
• re.sub()---In the target string every matched pattern will be replaced with provided replacement.
• re.subn()--- This function returns a tuple where first element is result string and second element is number of replacements.
• re.finditer()---Returns the iterator yielding a match object for each match. On each match object we can call start(), end()
and group() functions.
• re.compile()---
• ^ symbol--We can use ^ symbol to check whether the given target string starts with our provided pattern or not. if the target
string starts with Learn then it will return Match object,otherwise returns None.
• $ symbol--We can use $ symbol to check whether the given target string ends with our provided pattern or not

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